You will get High-Impact Image Annotation for Object Detection | Roboflow & YOLO
Project details
I provide accurate image annotation for object detection using Roboflow, delivering AI-ready datasets for YOLO, COCO, or VOC. With experience on multi-class projects like ECG sheet images, I create precise bounding boxes, organize datasets, and validate all annotations to ensure your machine learning models train faster and perform better.
My workflow includes project review, annotation setup, precise labeling, quality validation, and dataset export, with optional dataset documentation for larger projects. I specialize in multi-class datasets for medical imaging, autonomous systems, retail, and general computer vision, providing clean, reliable, and ready-to-use data.
Choose me for fast delivery, meticulous attention to detail, and high-quality annotations that accelerate your AI projects and improve model accuracy. Let’s turn your images into impactful, AI-ready datasets today!
My workflow includes project review, annotation setup, precise labeling, quality validation, and dataset export, with optional dataset documentation for larger projects. I specialize in multi-class datasets for medical imaging, autonomous systems, retail, and general computer vision, providing clean, reliable, and ready-to-use data.
Choose me for fast delivery, meticulous attention to detail, and high-quality annotations that accelerate your AI projects and improve model accuracy. Let’s turn your images into impactful, AI-ready datasets today!
Machine Learning Tools
Python, Python Scikit-Learn, PyTorch, TensorFlowWhat's included
| Service Tiers |
Starter
$50
|
Standard
$120
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 2 days | 5 days | 10 days |
Number of Revisions | 2 | 3 | 5 |
Model Validation/Testing | - | ||
Model Documentation | - | - | |
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$10 - $20
Additional Revision
+$10Frequently asked questions
About Vaishnavi
AI Engineer | Computer Vision, GANs (Pix2Pix), Sensor ML
Pune, India - 10:36 am local time
Most ML projects fail at deployment.
I focus on building systems that are accurate, scalable, and actually usable.
🚀 What I can help you with:
✔ Computer Vision (object detection, segmentation, GANs)
✔ Generative AI (Pix2Pix, Stable Diffusion workflows)
✔ Sensor-based ML (IMU, ToF, thermal data fusion)
✔ End-to-end pipelines (data → features → model → deployment)
🔥 Selected Work:
→ Built a gesture recognition system using IMU + ToF + thermal sensors with robust handling of missing sensor data, achieving ~90%+ accuracy across test data
→ Developed Pix2Pix pipelines for image-to-image transformation (segmentation, structured outputs)
→ Engineered feature pipelines using quaternion math + Kalman filtering for noisy real-world signals
→ Designed multimodal ML systems combining vision + sensor inputs
🧠 How I work:
→ I prioritize real-world performance over academic results
→ I write clean, maintainable, production-ready code
→ I communicate clearly and iterate fast
💡 Why clients hire me:
→ I bridge the gap between research-level ML and real-world deployment
→ I don’t just build models — I build usable AI systems
→ I can take your idea from concept → working solution
📩 Have an idea or stuck with an ML problem?
Let’s talk — I’ll help you turn it into a working system.
“Happy to build a small demo/prototype before starting!”
Steps for completing your project
After purchasing the project, send requirements so Vaishnavi can start the project.
Delivery time starts when Vaishnavi receives requirements from you.
Vaishnavi works on your project following the steps below.
Revisions may occur after the delivery date.
Project Review & Dataset Understanding
I carefully review your dataset, understand the object classes, labeling rules, and project requirements, and clarify any uncertainties before starting to ensure accurate annotations from the start.
Annotation Setup in Roboflow
I set up your project in Roboflow, configure classes, create annotation workflows, and ensure all images are ready for precise bounding box labeling compatible with YOLO, COCO, or VOC formats.